I'm well aware that there are already some articles on that topic, some people asked me to share some of my knowledge on this topic. Please take a look at this first part and let me know if you find this useful. If yes, I'm going to continue on writing more parts using more and more complicated expressions - if you have questions or problems that you think could be solved through regular expression, please post them.

Introduction

Oracle has always provided some character/string functions in its PL/SQL command set, such as SUBSTR, REPLACE or TRANSLATE. With 10g, Oracle finally gave us, the users, the developers and of course the DBAs regular expressions. However, regular expressions, due to their sometimes cryptic rules, seem to be overlooked quite often, despite the existence of some very interesing use cases. Beeing one of the advocates of regular expression, I thought I'll give the interested audience an introduction to these new functions in several installments.

Having fun with regular expressions - Part 1

Oracle offers the use of regular expression through several functions: REGEXP_INSTR, REGEXP_SUBSTR, REGEXP_REPLACE and REGEXP_LIKE. The second part of each function already gives away its purpose: INSTR for finding a position inside a string, SUBSTR for extracting a part of a string, REPLACE for replacing parts of a string. REGEXP_LIKE is a special case since it could be compared to the LIKE operator and is therefore usually used in comparisons like IF statements or WHERE clauses.

Regular expressions excel, in my opinion, in search and extraction of strings, using that for finding or replacing certain strings or check for certain formatting criterias. They're not very good at formatting strings itself, except for some special cases I'm going to demonstrate.

If you're not familiar with regular expression, you should take a look at the definition in Oracle's user guide Using Regular Expressions With Oracle Database, and please note that there have been some changes and advancements in 10g2. I'll provide examples, that should work on both versions.

Some of you probably already encountered this problem: checking a number inside a string, because, for whatever reason, a column was defined as VARCHAR2 and not as NUMBER as one would have expected.

Let's check for all rows where column col1 does NOT include an unsigned integer. I'll use this SELECT for demonstrating different values and search patterns:

Let's take a look at the 2nd argument of this REGEXP function: '^[0-9]+$'. Translated it would mean: start at the beginning of the string, check if there's one or more characters in the range between '0' and '9' (also called a matching character list) until the end of this string. "^", "[", "]", "+", "$" are all Metacharacters.

To understand regular expressions, you have to "think" in regular expressions. Each regular expression tries to "fit" an available string into its pattern and returns a result beeing successful or not, depending on the function. The "art" of using regular expressions is to construct the right search pattern for a certain task. Using functions like TRANSLATE or REPLACE did already teach you using search patterns, regular expressions are just an extension to this paradigma. Another side note: most of the search patterns are placeholders for single characters, not strings.

I'll take this example a bit further. What would happen if we would remove the "$" in our example? "$" means: (until the) end of a string. Without this, this expression would only search digits from the beginning until it encounters either another character or the end of the string. So this time, '123x' would be removed from the SELECTION since it does fit into the pattern.

Another change: we will keep the "$" but remove the "^". This character has several meanings, but in this case it declares: (start from the) beginning of a string. Without it, the function will search for a part of a string that has only digits until the end of the searched string. 'x123' would now be removed from our selection.

Now there's a question: what happens if I remove both, "^" and "$"? Well, just think about it. We now ask to find any string that contains at least one or more digits, so both '123x' and 'x123' will not show up in the result.

So what if I want to look for signed integer, since "+" is also used for a search expression. Escaping is the name of the game. We'll just use '^\+[0-9]+$' Did you notice the "\" before the first "+"? This is now a search pattern for the plus sign.

Should signed integers include negative numbers as well? Of course they should, and I'll once again use a matching character list. In this list, I don't need to do escaping, although it is possible. The result string would now look like this: '^[+-]?[0-9]+$'. Did you notice the "?"? This is another metacharacter that changes the placeholder for plus and minus to an optional placeholder, which means: if there's a "+" or "-", that's ok, if there's none, that's also ok. Only if there's a different character, then again the search pattern will fail.

Addendum: From this on, I found a mistake in my examples. If you would have tested my old examples with test data that would have included multiple signs strings, like "--", "-+", "++", they would have been filtered by the SELECT statement. I mistakenly used the "*" instead of the "?" operator. The reason why this is a bad idea, can also be found in the user guide: the "*" meta character is defined as 0 to multiple occurrences.

Looking at the values, one could ask the question: what about the integers with a trailing sign? Quite simple, right? Let's just add another '[+-] and the search pattern would look like this: '^[+-]?[0-9]+[+-]?$'.

Wait a minute, what happened to the row with the column value "-1-"?

You probably already guessed it: the new pattern qualifies this one also as a valid string. I could now split this pattern into several conditions combined through a logical OR, but there's something even better: a logical OR inside the regular expression. It's symbol is "|", the pipe sign.

Changing the search pattern again to something like this '^[+-]?[0-9]+$|^[0-9]+[+-]?$' [1] would return now the "-1-" value. Do I have to duplicate the same elements like "^" and "$", what about more complicated, repeating elements in future examples? That's where subexpressions/grouping comes into play. If I want only certain parts of the search pattern using an OR operator, we can put those inside round brackets. '^([+-]?[0-9]+|[0-9]+[+-]?)$' serves the same purpose and allows for further checks without duplicating the whole pattern.

Now looking for integers is nice, but what about decimal numbers? Those may be a bit more complicated, but all I have to do is again to think in (meta) characters. I'll just use an example where the decimal point is represented by ".", which again needs escaping, since it's also the place holder in regular expressions for "any character".

Valid decimals in my example would be ".0", "0.0", "0.", "0" (integer of course) but not ".". If you want, you can test it with the TO_NUMBER function. Finding such an unsigned decimal number could then be formulated like this: from the beginning of a string we will either allow a decimal point plus any number of digits OR at least one digits plus an optional decimal point followed by optional any number of digits. Think about it for a minute, how would you formulate such a search pattern?

Compare your solution to this one:

'^(\.[0-9]+|[0-9]+(\.[0-9]*)?)$'

Addendum: Here I have to use both "?" and "*" to make sure, that I can have 0 to many digits after the decimal point, but only 0 to 1 occurrence of this substrings. Otherwise, strings like "1.9.9.9" would be possible, if I would write it like this:

'^(\.[0-9]+|[0-9]+(\.[0-9]*)*)$'

Some of you now might say: Hey, what about signed decimal numbers? You could of course combine all the ideas so far and you will end up with a very long and almost unreadable search pattern, or you start combining several regular expression functions. Think about it: Why put all the search patterns into one function? Why not split those into several steps like "check for a valid decimal" and "check for sign".

From this select, the only rows I need to find are those with the column values "." and "-1.1-". I'll start this with a check for valid signs. Since I want to combine this with the check for valid decimals, I'll first try to extract a substring with valid signs through the REGEXP_SUBSTR function:

NVL(REGEXP_SUBSTR(t.col1, '^([+-]?[^+-]+|[^+-]+[+-]?)$'), ' ')

Remember the OR operator and the matching character collections? But several "^"? Some of the meta characters inside a search pattern can have different meanings, depending on their positions and combination with other meta characters. In this case, the pattern translates into: from the beginning of the string search for "+" or "-" followed by at least another character that is not "+" or "-". The second pattern after the "|" OR operator does the same for a sign at the end of the string.

This only checks for a sign but not if there also only digits and a decimal point inside the string. If the search string fails, for example when we have more than one sign like in the "-1.1-", the function returns NULL. NULL and LIKE don't go together very well, so we'll just add NVL with a default value that tells the LIKE to ignore this string, in this case a space.

All we have to do now is to combine the check for the sign and the check for a valid decimal number, but don't forget an option for the signs at the beginning or end of the string, otherwise your second check will fail on the signed decimals. Are you ready?

Excellent write up CD. Very nice indeed. Hopefully you'll be completing parts 2 and 3 some time soon. And with any luck, your article will encourage others to do the same....I know there's a few I'd like to see and a few I'd like to have a go at writing too :-)